Karthikeyan Singaravelan 6189cd6861
Import ABC from collections.abc for Python 3.9+ compatibility (#330)
* Import ABC from collections.abc instead of collections for Python 3.9 compatibility.

* Fix deprecation warnings due to invalid escape sequences.

* Support Python 3.10

Co-authored-by: Karl Kroening <karlk@kralnet.us>
2022-03-07 01:46:52 -08:00
..
2019-08-04 15:18:55 -07:00
2018-11-25 04:36:55 -06:00
2018-06-27 23:37:39 -07:00
2018-07-13 04:43:56 +02:00
2018-06-27 23:37:39 -07:00
2018-06-27 23:37:39 -07:00
2018-07-13 04:43:56 +02:00
2018-06-27 23:37:39 -07:00
2018-06-02 02:17:56 -07:00
2018-11-25 21:32:04 -06:00
2018-06-02 02:17:56 -07:00
2018-06-02 02:17:56 -07:00

Examples

Get video info (ffprobe)

probe = ffmpeg.probe(args.in_filename)
video_stream = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None)
width = int(video_stream['width'])
height = int(video_stream['height'])

Generate thumbnail for video

get-video-thumbnail graph
(
    ffmpeg
    .input(in_filename, ss=time)
    .filter('scale', width, -1)
    .output(out_filename, vframes=1)
    .run()
)

Convert video to numpy array

ffmpeg-numpy graph
out, _ = (
    ffmpeg
    .input('in.mp4')
    .output('pipe:', format='rawvideo', pix_fmt='rgb24')
    .run(capture_stdout=True)
)
video = (
    np
    .frombuffer(out, np.uint8)
    .reshape([-1, height, width, 3])
)

Read single video frame as jpeg through pipe

read-frame-as-jpeg graph
out, _ = (
    ffmpeg
    .input(in_filename)
    .filter('select', 'gte(n,{})'.format(frame_num))
    .output('pipe:', vframes=1, format='image2', vcodec='mjpeg')
    .run(capture_stdout=True)
)

Convert sound to raw PCM audio

transcribe graph
out, _ = (ffmpeg
    .input(in_filename, **input_kwargs)
    .output('-', format='s16le', acodec='pcm_s16le', ac=1, ar='16k')
    .overwrite_output()
    .run(capture_stdout=True)
)

Assemble video from sequence of frames

glob
(
    ffmpeg
    .input('/path/to/jpegs/*.jpg', pattern_type='glob', framerate=25)
    .output('movie.mp4')
    .run()
)

With additional filtering:

glob-filter
(
    ffmpeg
    .input('/path/to/jpegs/*.jpg', pattern_type='glob', framerate=25)
    .filter('deflicker', mode='pm', size=10)
    .filter('scale', size='hd1080', force_original_aspect_ratio='increase')
    .output('movie.mp4', crf=20, preset='slower', movflags='faststart', pix_fmt='yuv420p')
    .view(filename='filter_graph')
    .run()
)

Audio/video pipeline

av-pipeline graph
in1 = ffmpeg.input('in1.mp4')
in2 = ffmpeg.input('in2.mp4')
v1 = in1.video.hflip()
a1 = in1.audio
v2 = in2.video.filter('reverse').filter('hue', s=0)
a2 = in2.audio.filter('areverse').filter('aphaser')
joined = ffmpeg.concat(v1, a1, v2, a2, v=1, a=1).node
v3 = joined[0]
a3 = joined[1].filter('volume', 0.8)
out = ffmpeg.output(v3, a3, 'out.mp4')
out.run()

Mono to stereo with offsets and video

mono-to-stereo graph
audio_left = (
    ffmpeg
    .input('audio-left.wav')
    .filter('atrim', start=5)
    .filter('asetpts', 'PTS-STARTPTS')
)

audio_right = (
    ffmpeg
    .input('audio-right.wav')
    .filter('atrim', start=10)
    .filter('asetpts', 'PTS-STARTPTS')
)

input_video = ffmpeg.input('input-video.mp4')

(
    ffmpeg
    .filter((audio_left, audio_right), 'join', inputs=2, channel_layout='stereo')
    .output(input_video.video, 'output-video.mp4', shortest=None, vcodec='copy')
    .overwrite_output()
    .run()
)

Jupyter Frame Viewer

jupyter screenshot

Jupyter Stream Editor

jupyter demo

Tensorflow Streaming

tensorflow streaming; challenge mode: combine this with the webcam example below
  • Decode input video with ffmpeg
  • Process video with tensorflow using "deep dream" example
  • Encode output video with ffmpeg
process1 = (
    ffmpeg
    .input(in_filename)
    .output('pipe:', format='rawvideo', pix_fmt='rgb24', vframes=8)
    .run_async(pipe_stdout=True)
)

process2 = (
    ffmpeg
    .input('pipe:', format='rawvideo', pix_fmt='rgb24', s='{}x{}'.format(width, height))
    .output(out_filename, pix_fmt='yuv420p')
    .overwrite_output()
    .run_async(pipe_stdin=True)
)

while True:
    in_bytes = process1.stdout.read(width * height * 3)
    if not in_bytes:
        break
    in_frame = (
        np
        .frombuffer(in_bytes, np.uint8)
        .reshape([height, width, 3])
    )

    # See examples/tensorflow_stream.py:
    out_frame = deep_dream.process_frame(in_frame)

    process2.stdin.write(
        out_frame
        .astype(np.uint8)
        .tobytes()
    )

process2.stdin.close()
process1.wait()
process2.wait()
deep dream streaming

FaceTime webcam input (OS X)

(
    ffmpeg
    .input('FaceTime', format='avfoundation', pix_fmt='uyvy422', framerate=30)
    .output('out.mp4', pix_fmt='yuv420p', vframes=100)
    .run()
)

Stream from a local video to HTTP server

video_format = "flv"
server_url = "http://127.0.0.1:8080"

process = (
    ffmpeg
    .input("input.mp4")
    .output(
        server_url, 
        codec = "copy", # use same codecs of the original video
        listen=1, # enables HTTP server
        f=video_format)
    .global_args("-re") # argument to act as a live stream
    .run()
)

to receive the video you can use ffplay in the terminal:

$ ffplay -f flv http://localhost:8080

Stream from RTSP server to TCP socket

packet_size = 4096

process = (
    ffmpeg
    .input('rtsp://%s:8554/default')
    .output('-', format='h264')
    .run_async(pipe_stdout=True)
)

while process.poll() is None:
    packet = process.stdout.read(packet_size)
    try:
        tcp_socket.send(packet)
    except socket.error:
        process.stdout.close()
        process.wait()
        break